Modern inventory systems and sorting systems, such as those in mail order warehouses, supply chain distribution centers, and custom-order manufacturing facilities, face significant challenges in responding to requests for storage or retrieval of inventory items. As inventory systems grow, the challenges of simultaneously completing a large number of packing, storing, and other inventory-related tasks become non-trivial. In inventory systems tasked with responding to large numbers of diverse inventory requests, inefficient utilization of system resources, including space, equipment, and manpower, can result in lower throughput, unacceptably long response times, an ever-increasing backlog of unfinished tasks, and, in general, poor system performance. Additionally, expanding or reducing the size or capabilities of many inventory systems requires significant changes to existing infrastructure and equipment. As a result, the cost of incremental changes to capacity or functionality may be prohibitively expensive, limiting the ability of the system to accommodate fluctuations in system throughput.
One strategy for increasing the efficiency of modern inventory system is to automate some portion of the inventory management tasks, including storing, sorting, and retrieving items. To that end, material handling systems have been devised that incorporate significant spans of floor space or vertical storage space that are frequented by autonomous or semi-autonomous robotic units. In order to maintain the operation of such systems, computerized controllers designate tasks for the various robotic units, while tracking their progress and forecasted locations in order to prevent collisions and to monitor the availability of units for new tasks. These systems, however, may operate based on inaccurate data when an autonomous unit has ceased functioning within the material handling system, or when an autonomous unit has been removed from use in the system without appropriate updates to the controller.